Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful?
Research into women’s competitive soccer matches has shown distance and high-speed running (HSR) reductions over time, but the effects on some GPS-derived metrics have not been investigated. The purpose of this project was to examine the utility of common GPS metrics for indicating fatigue from the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Sports |
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| Online Access: | https://www.mdpi.com/2075-4663/12/1/9 |
| _version_ | 1797342547983466496 |
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| author | Benjamin J. Snyder Cameron Maung-Maung Cameron Whitacre |
| author_facet | Benjamin J. Snyder Cameron Maung-Maung Cameron Whitacre |
| author_sort | Benjamin J. Snyder |
| collection | DOAJ |
| description | Research into women’s competitive soccer matches has shown distance and high-speed running (HSR) reductions over time, but the effects on some GPS-derived metrics have not been investigated. The purpose of this project was to examine the utility of common GPS metrics for indicating fatigue from the T-SAFT<sup>90</sup> match simulation in collegiate soccer players. Unlike in competitive matches, changes to these metrics occurred as early as 15 min, with HSR, average and max speed, and speed intensity (SI) exhibiting significant declines. HSR and SI were even further decreased in later periods, with HSR lower in minutes 30–40 (T<sub>30–35</sub> and T<sub>35–40</sub>) than T<sub>15–20</sub> and lower in T<sub>70–85</sub> than T<sub>45–60</sub>. SI showed a similar pattern of continued decline, reaching its lowest value in the last three time segments. Accelerations and decelerations were also decreased beginning at T<sub>15–20</sub> and T<sub>20–25</sub>, respectively, but the fatigue index (FI), dynamic stress load (DSL), and step balance (SB) were unchanged. It can be concluded that in contrast to competitive matches where players can dictate their own intensity, a match simulation may result in a quicker onset of fatigue, but not all GPS-derived values change as expected in fatiguing environments. Coaches and sports scientists may use these findings to properly monitor fatigue in real time. |
| first_indexed | 2024-03-08T10:34:48Z |
| format | Article |
| id | doaj.art-d15ee9c47b6440c3ba2c3b60e46e2052 |
| institution | Directory Open Access Journal |
| issn | 2075-4663 |
| language | English |
| last_indexed | 2024-03-08T10:34:48Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sports |
| spelling | doaj.art-d15ee9c47b6440c3ba2c3b60e46e20522024-01-26T18:29:35ZengMDPI AGSports2075-46632023-12-01121910.3390/sports12010009Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful?Benjamin J. Snyder0Cameron Maung-Maung1Cameron Whitacre2Department of Health Sciences, Furman University, Greenville, SC 29613, USADepartment of Health Sciences, Furman University, Greenville, SC 29613, USASchool of Medicine Greenville, University of South Carolina, 607 Grove Rd., Greenville, SC 29605, USAResearch into women’s competitive soccer matches has shown distance and high-speed running (HSR) reductions over time, but the effects on some GPS-derived metrics have not been investigated. The purpose of this project was to examine the utility of common GPS metrics for indicating fatigue from the T-SAFT<sup>90</sup> match simulation in collegiate soccer players. Unlike in competitive matches, changes to these metrics occurred as early as 15 min, with HSR, average and max speed, and speed intensity (SI) exhibiting significant declines. HSR and SI were even further decreased in later periods, with HSR lower in minutes 30–40 (T<sub>30–35</sub> and T<sub>35–40</sub>) than T<sub>15–20</sub> and lower in T<sub>70–85</sub> than T<sub>45–60</sub>. SI showed a similar pattern of continued decline, reaching its lowest value in the last three time segments. Accelerations and decelerations were also decreased beginning at T<sub>15–20</sub> and T<sub>20–25</sub>, respectively, but the fatigue index (FI), dynamic stress load (DSL), and step balance (SB) were unchanged. It can be concluded that in contrast to competitive matches where players can dictate their own intensity, a match simulation may result in a quicker onset of fatigue, but not all GPS-derived values change as expected in fatiguing environments. Coaches and sports scientists may use these findings to properly monitor fatigue in real time.https://www.mdpi.com/2075-4663/12/1/9pacingT-SAFT<sup>90</sup>high-speed runningaccelerationsdecelerationsspeed intensity |
| spellingShingle | Benjamin J. Snyder Cameron Maung-Maung Cameron Whitacre Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful? Sports pacing T-SAFT<sup>90</sup> high-speed running accelerations decelerations speed intensity |
| title | Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful? |
| title_full | Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful? |
| title_fullStr | Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful? |
| title_full_unstemmed | Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful? |
| title_short | Indicators of Fatigue during a Soccer Match Simulation Using GPS-Derived Workload Values: Which Metrics Are Most Useful? |
| title_sort | indicators of fatigue during a soccer match simulation using gps derived workload values which metrics are most useful |
| topic | pacing T-SAFT<sup>90</sup> high-speed running accelerations decelerations speed intensity |
| url | https://www.mdpi.com/2075-4663/12/1/9 |
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